File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Genome-wide screening and cohorts validation identifying novel lncRNAs as prognostic biomarkers for clear cell renal cell carcinoma

TitleGenome-wide screening and cohorts validation identifying novel lncRNAs as prognostic biomarkers for clear cell renal cell carcinoma
Authors
Keywordsclear cell renal cell carcinoma
long noncoding RNAs
prognostic
survival analysis
Issue Date2020
Citation
Journal of Cellular Biochemistry, 2020, v. 121, n. 3, p. 2559-2570 How to Cite?
AbstractClear cell renal cell carcinoma (ccRCC) is the main subtype of renal cell carcinoma with varied prognosis. We aimed to identify and assess the possible prognostic long noncoding RNA (lncRNA) biomarkers. LncRNAs expression data and corresponding clinical information of 619 ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes analysis, univariate Cox regression, the least absolute shrinkage and selection operator Cox regression model were utilized to identify hub lncRNAs. Multivariate Cox regression was used to establish the risk model. Statistical analysis was performed using R 3.5.3. The expression value of five lncRNAs and the risk-score levels were significantly associated with a survival prognosis of ccRCC patients (all P <.001). In the TCGA validation cohort, the area under the curve (AUC) for the integrated nomogram was 0.905 and 0.91 for 3-, 5-year prediction separately. The AUC reached up to 0.757 in an independent ICGC cohort. Besides, the calibration plots also illustrated well curve-fitting between observation values and predictive values. Weighted gene co-expression network analysis and subsequent pathway analysis revealed that the PI3K-Akt-mTOR and hypoxia-inducible factor signaling crosstalk might function as the most essential mechanisms related to the five-lncRNAs signature. Our study suggested that lncRNA AC009654.1, AC092490.2, LINC00524, LINC01234, and LINC01885 were significantly associated with ccRCC prognosis. The prognostic model based on this five lncRNA may predict the overall survival of ccRCC.
Persistent Identifierhttp://hdl.handle.net/10722/314359
ISSN
2023 Impact Factor: 3.0
2023 SCImago Journal Rankings: 0.768
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Chuanjie-
dc.contributor.authorHuang, Da-
dc.contributor.authorLiu, Ao-
dc.contributor.authorXu, Yang-
dc.contributor.authorNa, Rong-
dc.contributor.authorXu, Danfeng-
dc.date.accessioned2022-07-20T12:03:45Z-
dc.date.available2022-07-20T12:03:45Z-
dc.date.issued2020-
dc.identifier.citationJournal of Cellular Biochemistry, 2020, v. 121, n. 3, p. 2559-2570-
dc.identifier.issn0730-2312-
dc.identifier.urihttp://hdl.handle.net/10722/314359-
dc.description.abstractClear cell renal cell carcinoma (ccRCC) is the main subtype of renal cell carcinoma with varied prognosis. We aimed to identify and assess the possible prognostic long noncoding RNA (lncRNA) biomarkers. LncRNAs expression data and corresponding clinical information of 619 ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes analysis, univariate Cox regression, the least absolute shrinkage and selection operator Cox regression model were utilized to identify hub lncRNAs. Multivariate Cox regression was used to establish the risk model. Statistical analysis was performed using R 3.5.3. The expression value of five lncRNAs and the risk-score levels were significantly associated with a survival prognosis of ccRCC patients (all P <.001). In the TCGA validation cohort, the area under the curve (AUC) for the integrated nomogram was 0.905 and 0.91 for 3-, 5-year prediction separately. The AUC reached up to 0.757 in an independent ICGC cohort. Besides, the calibration plots also illustrated well curve-fitting between observation values and predictive values. Weighted gene co-expression network analysis and subsequent pathway analysis revealed that the PI3K-Akt-mTOR and hypoxia-inducible factor signaling crosstalk might function as the most essential mechanisms related to the five-lncRNAs signature. Our study suggested that lncRNA AC009654.1, AC092490.2, LINC00524, LINC01234, and LINC01885 were significantly associated with ccRCC prognosis. The prognostic model based on this five lncRNA may predict the overall survival of ccRCC.-
dc.languageeng-
dc.relation.ispartofJournal of Cellular Biochemistry-
dc.subjectclear cell renal cell carcinoma-
dc.subjectlong noncoding RNAs-
dc.subjectprognostic-
dc.subjectsurvival analysis-
dc.titleGenome-wide screening and cohorts validation identifying novel lncRNAs as prognostic biomarkers for clear cell renal cell carcinoma-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/jcb.29478-
dc.identifier.pmid31646670-
dc.identifier.scopuseid_2-s2.0-85074612625-
dc.identifier.volume121-
dc.identifier.issue3-
dc.identifier.spage2559-
dc.identifier.epage2570-
dc.identifier.eissn1097-4644-
dc.identifier.isiWOS:000491954700001-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats